A model-based approach to segmentation of vascular and cardiac images is presented in an article by A. F. Frangi et al entitled “Model-Based Quantification of 3-D Magnetic Resonance Angiographic Images” in IEEE Transactions on Medical Imaging, Vol. 18, No. 10, 1999, pages 946-956, hereinafter referred to as Ref. 1. The paper describes two-step model-based vessel segmentation. First, a representation of the central vessel axis, hereinafter also referred to as the vessel centerline, is obtained. The model vessel centerline is described using a B-spline curve of degree n with s+1 control points. The model vessel centerline is adapted to the centerline of the vessel comprised in the image by minimizing an energy function, also referred to as a cost function or an objective function. The energy function comprises an external term and an internal energy term. The internal energy term comprises a stretching energy term and a bending energy term. The stretching energy term and the bending energy term define internal constraints on the deformation of the vessel centerline. The external energy term defines attraction of the vessel centerline to 3-D image features which are likely to lie on the central axis of the vessel. A vesselness filter described in an article by A. F. Frangi et al entitled “Multiscale vessel enhancement filtering”, in Medical Image Computing and Computer Assisted Intervention—MICCAI'98, W. M. Wells, A. Colchester and S. L. Delp (Eds.), Lecture Notes in Computer Science, Vol. 1496—Springer Verlag, Berlin, Germany, pages 130-137, hereinafter referred to as Ref. 2, is employed.